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Mapping interindividual dynamics of innate immune response at single-cell resolution

Lookup NU author(s): Emily Stephenson, Dr Gary Reynolds, Professor Muzlifah Haniffa

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).

Abstract

© 2023, The Author(s).Common genetic variants across individuals modulate the cellular response to pathogens and are implicated in diverse immune pathologies, yet how they dynamically alter the response upon infection is not well understood. Here, we triggered antiviral responses in human fibroblasts from 68 healthy donors, and profiled tens of thousands of cells using single-cell RNA-sequencing. We developed GASPACHO (GAuSsian Processes for Association mapping leveraging Cell HeterOgeneity), a statistical approach designed to identify nonlinear dynamic genetic effects across transcriptional trajectories of cells. This approach identified 1,275 expression quantitative trait loci (local false discovery rate 10%) that manifested during the responses, many of which were colocalized with susceptibility loci identified by genome-wide association studies of infectious and autoimmune diseases, including the OAS1 splicing quantitative trait locus in a COVID-19 susceptibility locus. In summary, our analytical approach provides a unique framework for delineation of the genetic variants that shape a wide spectrum of transcriptional responses at single-cell resolution.

Publication metadata

Author(s): Kumasaka N, Rostom R, Huang N, Polanski K, Meyer KB, Patel S, Boyd R, Gomez C, Barnett SN, Panousis NI, Schwartzentruber J, Ghoussaini M, Lyons PA, Calero-Nieto FJ, Gottgens B, Barnes JL, Worlock KB, Yoshida M, Nikolic MZ, Stephenson E, Reynolds G, Haniffa M, Marioni JC, Stegle O, Hagai T, Teichmann SA

Publication type: Article

Publication status: Published

Journal: Nature Genetics

Year: 2023

Volume: 55

Issue: 6

Pages: 1066-1075

Print publication date: 01/06/2023

Online publication date: 12/06/2023

Acceptance date: 27/04/2023

Date deposited: 03/07/2023

ISSN (print): 1061-4036

ISSN (electronic): 1546-1718

Publisher: Nature Research

URL: https://doi.org/10.1038/s41588-023-01421-y

DOI: 10.1038/s41588-023-01421-y

PubMed id: 37308670

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